UAI 2009

76 papers

A Bayesian Framework for Community Detection Integrating Content and Link Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu

A Bayesian Sampling Approach to Exploration in Reinforcement Learning John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate

A Direct Method for Estimating a Causal Ordering in a Linear Non-Gaussian Acyclic Model Shohei Shimizu, Aapo Hyvärinen, Yoshinobu Kawahara

A Factorization Criterion for Acyclic Directed Mixed Graphs Thomas S. Richardson

A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games Miroslav Dudík, Geoffrey J. Gordon

A Uniqueness Theorem for Clustering Reza Zadeh, Shai Ben-David

Alternating Projections for Learning with Expectation Constraints Kedar Bellare, Gregory Druck, Andrew McCallum

Approximate Inference on Planar Graphs Using Loop Calculus and Belief Propagation Vicenç Gómez, Hilbert J. Kappen, Michael Chertkov

Bayesian Discovery of Linear Acyclic Causal Models Patrik O. Hoyer, Antti Hyttinen

Bayesian Multitask Learning with Latent Hierarchies Hal Daumé Iii

Bisimulation-Based Approximate Lifted Inference Prithviraj Sen, Amol Deshpande, Lise Getoor

BPR: Bayesian Personalized Ranking from Implicit Feedback Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme

Censored Exploration and the Dark Pool Problem Kuzman Ganchev, Michael J. Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan

Characterizing Predictable Classes of Processes Daniil Ryabko

Complexity Analysis and Variational Inference for Interpretation-Based Probabilistic Description Logic Fábio Gagliardi Cozman, Rodrigo Bellizia Polastro

Computing Posterior Probabilities of Structural Features in Bayesian Networks Jin Tian, Ru He

Conditional Probability Tree Estimation Analysis and Algorithms Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl

Constraint Processing in Lifted Probabilistic Inference Jacek Kisynski, David Poole

Convergent Message Passing Algorithms - A Unifying View Talya Meltzer, Amir Globerson, Yair Weiss

Convex Coding David M. Bradley, J. Andrew Bagnell

Convexifying the Bethe Free Energy Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman

Correlated Non-Parametric Latent Feature Models Finale Doshi-Velez, Zoubin Ghahramani

Counting Belief Propagation Kristian Kersting, Babak Ahmadi, Sriraam Natarajan

Deterministic POMDPs Revisited Blai Bonet

Distributed Parallel Inference on Large Factor Graphs Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David R. O'Hallaron

Domain Knowledge Uncertainty and Probabilistic Parameter Constraints Yi Mao, Guy Lebanon

Effects of Treatment on the Treated: Identification and Generalization Ilya Shpitser, Judea Pearl

Exact Structure Discovery in Bayesian Networks with Less Space Pekka Parviainen, Mikko Koivisto

Exploring Compact Reinforcement-Learning Representations with Linear Regression Thomas J. Walsh, Istvan Szita, Carlos Diuk, Michael L. Littman

First-Order Mixed Integer Linear Programming Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík

Generating Optimal Plans in Highly-Dynamic Domains Christian Fritz, Sheila A. McIlraith

Group Sparse Priors for Covariance Estimation Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy

Herding Dynamic Weights for Partially Observed Random Field Models Max Welling

Identifying Confounders Using Additive Noise Models Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf

Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn

Improving Compressed Counting Ping Li

Interpretation and Generalization of Score Matching Siwei Lyu

L2 Regularization for Learning Kernels Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

Learning Continuous-Time Social Network Dynamics Yu Fan, Christian R. Shelton

Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence Mathias Niepert

Lower Bound Bayesian Networks - An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks Daniel Andrade, Bernhard Sick

MAP Estimation of Semi-Metric MRFs via Hierarchical Graph Cuts M. Pawan Kumar, Daphne Koller

MAP Estimation, Message Passing, and Perfect Graphs Tony Jebara

Mean Field Variational Approximation for Continuous-Time Bayesian Networks Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman

Measuring Inconsistency in Probabilistic Knowledge Bases Matthias Thimm

Modeling Discrete Interventional Data Using Directed Cyclic Graphical Models Mark Schmidt, Kevin P. Murphy

Monolingual Probabilistic Programming Using Generalized Coroutines Oleg Kiselyov, Chung-chieh Shan

Most Relevant Explanation: Properties, Algorithms, and Evaluations Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim

Multi-Task Feature Learning via Efficient L2, 1-Norm Minimization Jun Liu, Shuiwang Ji, Jieping Ye

Multilingual Topic Models for Unaligned Text Jordan L. Boyd-Graber, David M. Blei

Multiple Source Adaptation and the Rényi Divergence Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

New Inference Strategies for Solving Markov Decision Processes Using Reversible Jump MCMC Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet

On Maximum a Posteriori Estimation of Hidden Markov Processes Armen E. Allahverdyan, Aram Galstyan

On Smoothing and Inference for Topic Models Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh

On the Identifiability of the Post-Nonlinear Causal Model Kun Zhang, Aapo Hyvärinen

Optimization of Structured Mean Field Objectives Alexandre Bouchard-Côté, Michael I. Jordan

Ordinal Boltzmann Machines for Collaborative Filtering Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh

Prediction Markets, Mechanism Design, and Cooperative Game Theory Vincent Conitzer

Probabilistic Structured Predictors Shankar Vembu, Thomas Gärtner, Mario Boley

Products of Hidden Markov Models: It Takes N>1 to Tango Graham W. Taylor, Geoffrey E. Hinton

Quantifying the Strategyproofness of Mechanisms via Metrics on Payoff Distributions Benjamin Lubin, David C. Parkes

Quantum Annealing for Clustering Kenichi Kurihara, Shu Tanaka, Seiji Miyashita

Quantum Annealing for Variational Bayes Inference Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita

REGAL: A Regularization Based Algorithm for Reinforcement Learning in Weakly Communicating MDPs Peter L. Bartlett, Ambuj Tewari

Regret-Based Reward Elicitation for Markov Decision Processes Kevin Regan, Craig Boutilier

Robust Graphical Modeling with T-Distributions Michael Finegold, Mathias Drton

Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making Mark Crowley, John Nelson, David Poole

Simulation-Based Game Theoretic Analysis of Keyword Auctions with Low-Dimensional Bidding Strategies Yevgeniy Vorobeychik

Temporal Action-Graph Games: A New Representation for Dynamic Games Albert Xin Jiang, Kevin Leyton-Brown, Avi Pfeffer

Temporal-Difference Networks for Dynamical Systems with Continuous Observations and Actions Christopher M. Vigorito

The Entire Quantile Path of a Risk-Agnostic SVM Classifier Jin Yu, S. V. N. Vishwanathan, Jian Zhang

The Infinite Latent Events Model David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum

The Temporal Logic of Causal Structures Samantha Kleinberg, Bud Mishra

Using the Gene Ontology Hierarchy When Predicting Gene Function Sara Mostafavi, Quaid Morris

Virtual Vector Machine for Bayesian Online Classification Thomas P. Minka, Rongjing Xiang, Yuan (Alan) Qi

Which Spatial Partition Trees Are Adaptive to Intrinsic Dimension? Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta